Network Traffic Intrusion Detection System Using Fuzzy Logic and Neural Network

Mrudul Dixit; Rajashwini Ukarande

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Network Traffic Intrusion Detection System Using Fuzzy Logic and Neural Network

机译：基于模糊逻辑和神经网络的网络流量入侵检测系统

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Intrusion Detection System (IDS) are actively used to identify any unusual activities in a network. To improve the effectiveness of IDS, security experts have embedded their extensive knowledge with the use of fuzzy logic, neuro-fuzzy, neural network and other such AI techniques. This article presents an intrusion detection system in network based on fuzzy logic and neural network. The proposed system is evaluated using the KDD Cup 99 dataset. The fuzzy system detects the intrusion behavior of the network using the defined set of rules. Whereas neural network trains the network based on the input and uses the trained system to predict the output. The evaluation depicts the effectiveness of the selected method in terms of selection of attributes which gives high True Positive Rate and True Negative Rate, with good precision in attack detection.

机译：入侵检测系统（IDS）被积极用于识别网络中的任何异常活动。为了提高IDS的有效性，安全专家使用模糊逻辑，神经模糊，神经网络和其他此类AI技术来嵌入其广泛的知识。本文提出了一种基于模糊逻辑和神经网络的网络入侵检测系统。建议的系统使用KDD Cup 99数据集进行评估。模糊系统使用定义的规则集来检测网络的入侵行为。而神经网络根据输入来训练网络，并使用经过训练的系统来预测输出。评估从属性选择的角度描述了所选方法的有效性，这些属性提供了较高的真实肯定率和真实否定率，并且在攻击检测中具有良好的精度。

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来源
《International journal of synthetic emotions》 |2017年第1期|1-17|共17页
作者
Mrudul Dixit; Rajashwini Ukarande;
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作者单位

Department of Electronics and Telecommunication, MKSSS's Cummins College of Engineering for Women, Pune, India;

Department of Electronics and Telecommunication, MKSSS's Cummins College of Engineering for Women, Pune, India;

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正文语种 eng
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关键词
Artificial Neural Network; Backpropagation Algorithm; Denial of Service; Fuzzy Logic; Intrusion Detection System (IDS); KDD Cup 99 Dataset; Probe;

机译：人工神经网络;反向传播算法;拒绝服务;模糊逻辑;入侵检测系统（IDS）;KDD Cup 99数据集;探测;

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2. A FUZZY NEURAL NETWORK AND MULTIPLE KERNEL FUZZY C-MEANS ALGORITHM FOR SECURED INTRUSION DETECTION SYSTEM [J] . P.ANANTHI, P.BALASUBRAMANIE Journal of Theoretical and Applied Information Technology . 2014,第1期

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3. Hardware Module Design and Software Implementation of Multisensor Fire Detection and Notification System Using Fuzzy Logic and Convolutional Neural Networks (CNNs) [J] . Robert A. Sowah, Kwaku Apeadu, Francis Gatsi, Journal of Engineering . 2020,第1期

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4. Intrusion detection system modeling based on neural networks and fuzzy logic [C] . A. Midzic, Z. Avdagic, S. Omanovic 20th Jubilee IEEE International Conference on Intelligent Engineering Systems . 2016

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6. Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security [O] . Min-Joo Kang, Je-Won Kang -1

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Network Traffic Intrusion Detection System Using Fuzzy Logic and Neural Network

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